Monitor MCP Server

A Mac system monitoring server based on the MCP protocol, which can monitor CPU, memory, and disk usage

Monitoring Developer tools #System monitoring #Performance analysis #Resource management .Python

rating : 2 points

downloads : 11

update time : 2025-04-29

What is Monitor MCP Server?

Monitor MCP Server is a lightweight system monitoring tool that provides real - time data on the hardware resource usage of Mac computers through the Message Control Protocol (MCP). It helps users understand the system's running status and detect performance bottlenecks in a timely manner.

How to use Monitor MCP Server?

After installation, the server will automatically run and collect system data. Users can connect to the server through an MCP client and send specific instructions to obtain monitoring data. The basic functions can be used without complex configuration.

Use cases

Suitable for scenarios such as developers testing application performance, system administrators monitoring server status, and ordinary users understanding the computer's resource usage. It is especially suitable for long - term resource monitoring.

Main features

CPU monitoringDisplay the usage rate, operating frequency, and the number of cores of each CPU core in real - time to help understand the processor load.

Memory monitoringProvide detailed information such as total memory, available memory, usage rate, and free memory to clearly show the memory usage status.

Disk monitoringMonitor the usage of each partition, including the file system type, total space, used space, and available space to prevent disk space shortage.

Advantages and limitations

Advantages

Lightweight design with low system resource consumption

Real - time data update with quick response

Support detailed monitoring of multi - core CPUs

Simple and easy - to - use MCP protocol interface

Limitations

Currently only supports the Mac system

Requires a Python environment to be installed

Lacks a graphical interface (needs to be used with a client)

How to use

Install dependencies

Ensure that Python and pip are installed on the system, and then install the required dependency libraries.

Start the server

Run the MCP server program to start collecting system data.

Connect the client

Use an MCP - compatible client to connect to the server and send monitoring instructions.

Usage examples

Monitor the performance of the development environmentDevelopers can monitor the CPU and memory usage when running large - scale projects to optimize the development environment configuration.

Server resource warningSystem administrators can set up scheduled tasks to check disk space to prevent service interruption due to insufficient space.